Systems and methods for compensating gradient pulse of MRI

ABSTRACT

A method for determining a flow sensitive gradient block includes determine a gradient parameter for one or more echoes in an imaging sequence according to a scanning protocol. The method also includes determining one or more time origins for gradient moment calculation based on the gradient parameter and obtaining one or more target zeroth-order gradient moments and one or more target first-order gradient moments corresponding to the one or more time origins. The method further includes determining one or more parameters of the one or more flow sensitive gradient blocks with respect to the one or more target zeroth-order gradient moments and the one or more target first-order gradient moment and updating the gradient parameter according to the one or more parameters of the one or more flow sensitive gradient blocks.

TECHNICAL FIELD

The present disclosure generally relates to a magnetic resonance imaging(MRI) system, and more particularly, relates to systems and methods forcompensating gradient pulse of MRI.

BACKGROUND

Magnetic resonance imaging (MRI) is a technology that makes use of oneor more gradient pluses to encode spatial information to MR signals forreconstructing images. The MRI technology has been widely used inmedical diagnosis. During a scanning process, fluid flow (e.g., blood orcerebrospinal fluid flow) may affect the spatial encoding to MR signals.It may be desirable to provide systems and methods for determining aflow sensitive gradient block accurately.

SUMMARY

According to an aspect of the present disclosure, a system may includeat least one non-transitory computer-readable storage medium including aset of instructions, and at least one processor in communication withthe at least one non-transitory computer-readable storage medium,wherein when executing the instructions, the at least one processor isconfigured to cause the system to determine an imaging gradientparameter according to a scanning protocol, determine a time origin forgradient moment calculation and a target condition for a flow sensitivegradient block associated with the time origin determine a parameter ofa flow sensitive gradient block according to the target condition, andadjust the imaging gradient parameter according to the parameter of theflow sensitive gradient block. In some embodiments, the flow sensitivegradient block may include at least one flow sensitive gradient. In someembodiments, the parameter of the flow sensitive gradient block mayinclude at least one duration and at least one amplitude value of the atleast one flow sensitive gradient.

In some embodiments, the flow sensitive gradient block may include afirst flow sensitive gradient and a second flow sensitive gradient.

In some embodiments, the target condition may include a targetzeroth-order gradient moment and a target first-order gradient momentassociated with the flow sensitive gradient block.

In some embodiments, the at least one processor may be configured tocause the system to initialize a first duration and a time differenceassociated with the flow sensitive gradient block, the first durationbeing a time length of the flow sensitive gradient block and the timedifference being a distance between the time origin and a time point ofthe flow sensitive gradient block.

In some embodiments, the at least one processor may be configured tocause the system to determine a first amplitude value of the first flowsensitive gradient and a second amplitude value of the second flowsensitive gradient, determine the first amplitude value and the secondamplitude value are equal to or less than a threshold, and in responseto the determination that the first amplitude value and the secondamplitude value are equal to or less than the threshold, determine thefirst duration as the duration of the flow sensitive gradient block.

In some embodiments, the at least one processor may be configured tocause the system to determine a first amplitude value of the first flowsensitive gradient and a second amplitude value of the second flowsensitive gradient, determine the first amplitude value and the secondamplitude value are larger than a threshold, and in response to thedetermination that the first amplitude value and the second amplitudevalue are larger than the threshold, determine a second duration byadjusting the first duration as the duration of the flow sensitivegradient block.

In some embodiments, the parameter of the flow sensitive gradient blockmay include a component on a slice selecting axis, a component on aphase encoding axis, and a component on a readout coordinate axis.

In some embodiments, the at least one processor may be configured tocause the system to determine an optimal duration associated with theslice selecting axis, an optimal duration associated with the phaseencoding axis, and an optimal duration associated with the readoutcoordinate axis and determine a shared duration for the phase encodingaxis, the phase encoding axis, and the readout coordinate axis based onthe optimal durations.

In some embodiments, the at least one processor may be configured tocause the system to determine modify the parameter of the flow sensitivegradient block based on the first duration, and insert the modified flowsensitive gradient block into the imaging gradient parameter.

In some embodiments, the scanning protocol may be associated to a pulsesequence of one or more echoes.

In some embodiments, the flow sensitive gradient block may be used toperform at least one function of flow encoding, flow compensation, orflow dephasing.

According to an aspect of the present disclosure, a method, implementedon a computing device having at least one processor, at least onecomputer-readable storage medium, and a communication port connected toan imaging device for determining, by the at least one processor, agradient parameter for a first echo in an imaging sequence according toa scanning protocol. The method may include determining, by the at leastone processor, a first time origin for gradient moment calculation basedon the gradient parameter. The method also include obtaining, by the atleast one processor, at least a target zeroth-order gradient moment anda target first-order gradient moment corresponding to the first timeorigin. The method may further include determining, by the at least oneprocessor, a first parameter of a first flow sensitive gradient blockwith respect to the target zeroth-order gradient moment and the targetfirst-order gradient moment. The method may also include updating, bythe at least one processor, the gradient parameter according to thefirst parameter of the first flow sensitive gradient block.

In some embodiments, the imaging sequence may be a single-echo sequence,and the gradient parameter may correspond to a single-pulse fieldgradient or a double-pulse field gradient.

In some embodiments, the first flow sensitive gradient block may includea first sensitive gradient and a second sensitive gradient. The methodmay further include initializing a first duration and a time differenceassociated with the first flow sensitive gradient block, the firstduration being a time length of the first flow sensitive gradient block,the time difference being a distance between the first time origin and atime point of the first flow sensitive gradient block.

In some embodiments, the method may further include determining a firstamplitude value of the first flow sensitive gradient and a secondamplitude value of the second flow sensitive gradient; determining thefirst amplitude value and the second amplitude value equal to or lessthan a threshold; and in response to the determination that the firstamplitude value and the second amplitude value are equal to or less thanthe threshold, determining the first duration as the duration of thefirst flow sensitive gradient block.

In some embodiments, the method may further include determining a firstamplitude value of the first flow sensitive gradient and a secondamplitude value of the second flow sensitive gradient; determining thefirst amplitude value and the second amplitude value are larger than athreshold; and in response to the determination that the first amplitudevalue and the second amplitude value are larger than the threshold,determining a second duration by adjusting the first duration as theduration of the first flow sensitive gradient block.

In some embodiments, the method may further include determining anoptimal duration associated with the slice selecting axis, an optimalduration associated with the phase encoding axis, and an optimalduration associated with the readout coordinate axis; and determining ashared duration for the phase encoding axis, the phase encoding axis,and the readout coordinate axis based on the optimal durations.

In some embodiments, the imaging sequence may further comprise a secondecho, and the method further include determining an imaging gradientparameter for the second echo; determining a second time origin for thegradient moment calculation based on the gradient parameter for thesecond echo; obtaining at least a target zeroth-order gradient momentand a target first-order gradient moment corresponding to the secondtime origin; determining a second parameter of a second flow sensitivegradient block with respect to the target zeroth-order gradient momentand the target first-order gradient moment; and updating the gradientparameter according to the second parameter of the second flow sensitivegradient block.

In some embodiments, the target zeroth-order gradient moment and thetarget first-order gradient moment corresponding to the first timeorigin are independent of the target zeroth-order gradient moment andthe target first-order gradient moment corresponding to the second timeorigin.

In some embodiments, the method further include exciting nuclear spinein a volume of a subject based on the updated gradient parameter, thevolume may comprise a flow; acquiring magnetic resonance signals for thevolume; and generating a magnetic resonance image of the volume with theflow based on the magnetic resonance signals.

According to another aspect of the present disclosure, a non-transitorycomputer readable medium embodying a computer program product may beprovided. The computer program product may include the instructions thatare configured to cause a computing device to determine an imaginggradient parameter for one or more echoes in the imaging sequence. Thecomputer program product may also include the instructions that areconfigured to cause the computing device to determine one or more timeorigins for gradient moment calculation based on the gradient parameterand obtain one or more target zeroth-order gradient moments and one ormore target first-order gradient moments corresponding to the one ormore time origins. The computer program product may further include theinstructions that are configured to cause the computing device todetermine one or more parameters of the one or more flow sensitivegradient blocks with respect to the one or more target zeroth-ordergradient moments and the one or more target first-order gradient momentand update the gradient parameter according to the one or moreparameters of the one or more flow sensitive gradient blocks.

Additional features will be set forth in part in the description whichfollows, and in part will become apparent to those skilled in the artupon examination of the following and the accompanying drawings or maybe learned by production or operation of the examples. The features ofthe present disclosure may be realized and attained by practice or useof various aspects of the methodologies, instrumentalities, andcombinations set forth in the detailed examples discussed below.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure is further described in terms of exemplaryembodiments. These exemplary embodiments are described in detail withreference to the drawings. These embodiments are non-limiting exemplaryembodiments, in which like reference numerals represent similarstructures throughout the several views of the drawings, and wherein:

FIG. 1 is a block diagram illustrating an exemplary imaging systemaccording to some embodiments of the present disclosure;

FIG. 2 is a block diagram illustrating an exemplary MR scanner accordingto some embodiments of the present disclosure;

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary computing device according to someembodiments of the present disclosure;

FIG. 4 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary mobile device on which a userterminal may be implemented according to some embodiments of the presentdisclosure;

FIG. 5 is a block diagram illustrating an exemplary processing engineaccording to some embodiments of the present disclosure;

FIG. 6 is a block diagram illustrating an exemplary processing moduleaccording to some embodiments of the present disclosure;

FIG. 7 is a flowchart illustrating an exemplary process for determininga flow sensitive gradient block according to some embodiments of thepresent disclosure;

FIG. 8 is a flowchart illustrating an exemplary process for determininga flow sensitive gradient block according to some embodiments of thepresent disclosure;

FIG. 9 is a flowchart illustrating an exemplary process for determininga flow sensitive gradient block according to some embodiments of thepresent disclosure;

FIG. 10-A illustrates exemplary diagrams of a single echo pulse sequenceaccording to some embodiments of the present disclosure;

FIG. 10-B illustrates exemplary diagrams of a single echo pulse sequenceaccording to some embodiments of the present disclosure;

FIG. 10-C illustrates exemplary diagrams of curves respecting tozeroth-order gradient moment M0 and first-order gradient moment M1varied with time according to some embodiments of the presentdisclosure;

FIG. 11-A illustrates exemplary diagrams of a double echo pulse sequenceaccording to some embodiments of the present disclosure;

FIG. 11-B illustrates exemplary diagrams of a double echo sequenceaccording to some embodiments of the present disclosure;

FIG. 11-C illustrates exemplary diagrams of curves respecting tozeroth-order gradient moment M0 and first-order gradient moment M1varied with time according to some embodiments of the presentdisclosure;

FIG. 12-A illustrates exemplary diagrams of a multi-echoes sequenceaccording to some embodiments of the present disclosure; and

FIG. 12-B illustrates exemplary diagrams of curves respecting tozeroth-order gradient moment M0 and first-order gradient moment M1varied with time according to some embodiments of the presentdisclosure.

DETAILED DESCRIPTION

The following description is presented to enable any person skilled inthe art to make and use the present disclosure, and is provided in thecontext of a particular application and its requirements. Variousmodifications to the disclosed embodiments will be readily apparent tothose skilled in the art, and the general principles defined herein maybe applied to other embodiments and applications without departing fromthe spirit and scope of the present disclosure. Thus, the presentdisclosure is not limited to the embodiments shown, but is to beaccorded the widest scope consistent with the claims.

The terminology used herein is for the purpose of describing particularexemplary embodiments only and is not intended to be limiting. As usedherein, the singular forms “a,” “an,” and “the” may be intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprise,”“comprises,” and/or “comprising,” “include,” “includes,” and/or“including,” when used in this specification, specify the presence ofstated features, integers, steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, steps, operations, elements, components,and/or groups thereof.

It will be understood that the term “system,” “engine,” “unit,” and/or“module” used herein are one method to distinguish different components,elements, parts, section or assembly of different level in ascendingorder. However, the terms may be displaced by other expression if theyachieve the same purpose.

Generally, the word “module” or “unit” as used herein, refers to logicembodied in hardware or firmware, or to a collection of softwareinstructions. A module or a unit described herein may be implemented assoftware and/or hardware and may be stored in any type of non-transitorycomputer-readable medium or other storage device. In some embodiments, asoftware module/unit may be compiled and linked into an executableprogram. It will be appreciated that software modules can be callablefrom other modules/units or from themselves, and/or may be invoked inresponse to detected events or interrupts. Software modules/unitsconfigured for execution on computing devices (e.g., processor 320 asillustrated in FIG. 3) may be provided on a computer-readable medium,such as a compact disc, a digital video disc, a flash drive, a magneticdisc, or any other tangible medium, or as a digital download (and can beoriginally stored in a compressed or installable format that needsinstallation, decompression, or decryption prior to execution). Suchsoftware code may be stored, partially or fully, on a storage device ofthe executing computing device, for execution by the computing device.Software instructions may be embedded in a firmware, such as an EPROM.It will be further appreciated that hardware modules/units may beincluded in connected logic components, such as gates and flip-flops,and/or can be included of programmable units, such as programmable gatearrays or processors. The modules/units or computing devicefunctionality described herein may be implemented as softwaremodules/units, but may be represented in hardware or firmware. Ingeneral, the modules/units described herein refer to logicalmodules/units that may be combined with other modules/units or dividedinto sub-modules/sub-units despite their physical organization orstorage. The description may be applicable to a system, an engine, or aportion thereof.

It will be understood that when a unit, engine or module is referred toas being “on,” “connected to,” or “coupled to,” another unit, engine, ormodule, it may be directly on, connected or coupled to, or communicatewith the other unit, engine, or module, or an intervening unit, engine,or module may be present, unless the context clearly indicatesotherwise. As used herein, the term “and/or” includes any and allcombinations of one or more of the associated listed items.

These and other features, and characteristics of the present disclosure,as well as the methods of operation and functions of the relatedelements of structure and the combination of parts and economies ofmanufacture, may become more apparent upon consideration of thefollowing description with reference to the accompanying drawings, allof which form a part of the present disclosure. It is to be expresslyunderstood, however, that the drawings are for the purpose ofillustration and description only and are not intended to limit thescope of the present disclosure. It is understood that the drawings arenot to scale.

The flowcharts used in the present disclosure illustrate operations thatsystems implement according to some embodiments of the presentdisclosure. It is to be expressly understood, the operations of theflowcharts may be implemented not in order. Conversely, the operationsmay be implemented in inverted order, or simultaneously. Moreover, oneor more other operations may be added to the flowcharts. One or moreoperations may be removed from the flowcharts.

FIG. 1 is a block schematic diagram illustrating an exemplary imagingsystem according to some embodiments of the present disclosure. Theimaging system 100 may be a magnetic resonance imaging (MRI) system, apositron emission tomography-magnetic resonance imaging (PET-MRI)system, a digital subtraction angiography-magnetic resonance, or thelike, or any combination thereof. For example, the mobile device 161 mayinclude a mobile phone, a personal digital assistance (PDA), a gamingdevice, a navigation device, a point of sale (POS) device, a laptop, atablet computer, a desktop, or the like, or any combination thereof. Insome embodiments, the terminal device 160 may include an input device,an output device, etc. The input device may include alphanumeric andother keys that may be input via a keyboard, a touch screen (forexample, with haptics or tactile feedback), a speech input, an eyetracking input, a brain monitoring system, or any other comparable inputmechanism. The input information received through the input device maybe transmitted to the processing engine 130 via, for example, a bus, forfurther processing. Other types of the input device may include a cursorcontrol device, such as a mouse, a trackball, or cursor direction keys,etc. The output device may include a display, a speaker, a printer, orthe like, or any combination thereof. In some embodiments, the terminaldevice 160 may be part of the processing engine 130.

This description is intended to be illustrative, and not to limit thescope of the present disclosure. Many alternatives, modifications, andvariations will be apparent to those skilled in the art. The features,structures, methods, and characteristics of the exemplary embodimentsdescribed herein may be combined in various ways to obtain additionaland/or alternative exemplary embodiments. For example, the storagedevice 150 may be a data storage including cloud computing platforms,such as, public cloud, private cloud, community, hybrid clouds, etc. Insome embodiments, the processing engine 130 may be integrated into theMR scanner 110. However, those variations and modifications do notdepart the scope of the present disclosure.

FIG. 2 is a block diagram illustrating an exemplary MR scanner accordingto some embodiments of the present disclosure. As shown in the FIG. 2,the MR scanner 110 may include a magnetic body 220, a gradient coil 230,an RF coil 240, a pulse sequence 250, a gradient control 260, and agradient driven 270.

The magnetic body 220 may generate a static magnetic field BO during anMRI process. The magnetic body 220 may be of various types including,for example, a permanent magnet, a superconducting electromagnet, aresistive electromagnet, etc.

The gradient coil 230 may generate magnetic field gradients to the mainmagnetic field BO in the X, Y, and/or Z directions (or axes). In someembodiments, the gradient coil 230 may include an X-direction coil (oraxis), a Y-direction coil (or axis), a Z-direction coil (or axis), etc.For example, the Z-direction coil may be designed based on circular(Maxwell) coil, while the X-direction coil and the Y-direction coil maybe designed on the basis of the saddle (Golay) coil configuration. Asused herein, the X direction may be also referred to as the readout (RO)direction (or a frequency encoding direction), the Y direction may bealso referred to the phase encoding (PE) direction, the Z direction maybe also referred to the slice selecting encoding (SPE) direction. In thepresent disclosure, the readout direction and the frequency encodingdirection may be used interchangeably.

The gradient magnetic fields may include a slice selecting encoding(SPE) gradient field corresponding to Z-direction, a phase encoding (PE)gradient field corresponding to Y-direction, a readout (RO) gradientfield corresponding to X-direction, etc. The gradient magnetic fields ondifferent directions may be used to encode the spatial information of MRsignals. In some embodiments, the gradient magnetic fields may be alsoused to perform at least one function of flow encoding, flowcompensation, flow dephasing, or the like, or any combination thereof.

The RF coil 240 may emit RF pulse signals to and/or receive MR signalsfrom a human body 210 being examined. In some embodiments, the RF coil240 may include an RF transmitting coil and an RF receiving coil. The RFtransmitting coil may emit RF pulse signals that may excite the nucleusin the human body 210 to resonate at the Larmor frequency. The RFreceiving coil may receive MR signals emitted from the human body 210.In some embodiments, the RF transmitting coil and RF receiving coil maybe integrated into one single coil, for example, atransmitting/receiving coil. The RF coil 240 may be of various typesincluding, for example, a QD orthogonal coil, a phase-array coil, aspecific element spectrum coil, etc. In some embodiments, the RF coil240 may be different according to different parts of a body beingexamined, for example, a head coil, a knee joint coil, a cervicalvertebra coil, a thoracic vertebra coil, a temporomandibular joint (TMJ)coil, etc. In some embodiments, according to function and size, the RFcoil 240 may be classified as a volume coil and a local coil. Forexample, the volume coil may include a birdcage coil, a transverseelectromagnetic coil, a surface coil, a saddle coil, etc. As anotherexample, the local coil may include a solenoid coil, a saddle coil, aflexible coil, etc.

The pulse sequence 250 may have several portions including, for example,an RF pulse, an MR signal, a phase encoding (PE) gradient, a readout(RO) gradient, a slice selecting encoding (SPE) gradient, etc. In someembodiments, the pulse sequence 250 may include a flow sensitivegradient block/module (hereinafter referred to as “flow sensitivegradient block”). The flow sensitive gradient block may be a flowsensitive gradient added to at least one directions corresponding to thephase encoding (PE) gradient, the readout (RO) gradient, or the sliceselecting encoding (SPE) gradient.

The pulse sequence 250 may be defined by imaging gradient parameters andarrangement in time sequence corresponding to the imaging gradientparameters. In some embodiments, the imaging gradient parameters mayinclude parameters related to an RF pulse emitted by the RF coil 240,the parameters related to gradient fields generated by the gradientscoil 230, and the time for collecting MR signals. The different portionsof the pulse sequence 250, such as (the RF pulse, the imaging gradient,etc.) may refer to different imaging gradient parameters. For example,the RF pulse block may refer to parameters related to an RF pulse, suchas a bandwidth (also referred to as a frequency range), an amplitude orstrength, a time for applying the RF pulse, a duration for applying theRF pulse, etc. The parameters related to the imaging gradient mayinclude an amplitude value of the gradient pulses, a duration of animaging gradient, a starting time for applying an imaging gradient, anending time for applying an imaging gradient, etc. The parametersrelated to the MR signals may include MR signals types, a number ofechoes, centers of the echoes, time of echoes, etc.

In some embodiments, the pulse sequence 250 may be a free-inductiondecay (FID) sequence, a spin echo (SE) sequence, a gradient echo (GRE)sequence, a fast imaging with stead-state precession (FISP) sequence, orthe like, or any combination thereof.

In some embodiments, the pulse sequence 250 may be connected to and/orcommunicate with the processing engine 130. For example, before an MRIscanning process, at least one portion of the pulse sequence 250 (e.g.,the RF pulse, the imaging gradient) may be designed and/or determined bythe processing engine 130 according to clinical demands or a scanningprotocol. In the MRI scanning process, the RF coil 240 may emit RFpulses with specific parameters related to the RF pulse of the pulsesequence 250, and receive MR signals. The MR signals may compose oneportion of the pulse sequence 250. The gradient control 260 may controlthe gradient driven 270 to drive the gradient coil 230 by gradientpulses with specific parameters related to the imaging gradient of thepulse sequence 250. The gradient fields generated by the gradient coil230 may encode the MR signals. The encoded MR signals may be transmittedto the processing engine 130 for determining an MR image.

This description is intended to be illustrative, and not to limit thescope of the present disclosure. Many alternatives, modifications, andvariations will be apparent to those skilled in the art. The features,structures, methods, and characteristics of the exemplary embodimentsdescribed herein may be combined in various ways to obtain additionaland/or alternative exemplary embodiments. For example, the MR scanner110 may include a sending channel and/or a receiving channel for sendingand receiving information (e.g., RF pulse, imaging gradient, etc.).However, those variations and modifications do not depart the scope ofthe present disclosure.

FIG. 3 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary computing device on which theprocessing engine 130 may be implemented according to some embodimentsof the present disclosure. The processing engine 130 may be implementedon the computing device via its hardware, software program, firmware, orany combination thereof. Although only one such computing device isshown, for convenience, the functions of the processing engine 130described in the present disclosure may be implemented in a distributedfashion on a number of similar platforms, to distribute the processingload. The processing engine 130 may include, among other things, aninternal communication bus 310, a processor 320, a program storage anddata storage of different forms (e.g., a disk 370, a read only memory(ROM) 330, or a random access memory (RAM) 340), for various data filesto be processed and/or communicated by the computer, as well as possiblyprogram instructions to be executed by processor 320. Aspects of themethods of the image processing and/or other processes, as outlinedherein, may be embodied in programming. Program aspects of thetechnology may be thought of as “products” or “articles of manufacture”typically in the form of executable code and/or associated data that iscarried on or embodied in a type of machine readable medium. Tangiblenon-transitory “storage” type media may include any or all of the memoryor other storage for the computers, processors, or the like, orassociated modules thereof, such as various semiconductor memories, tapedrives, disk drives and the like, which may provide storage at any timefor the software programming.

All or portions of the software may at times be communicated through anetwork such as the Internet or various other telecommunicationnetworks. Such communications, for example, may enable loading of thesoftware from one computer or processor into another, for example, froma management server or host computer of a mammography system into thehardware platform(s) of a computing environment or other systemimplementing a computing environment or similar functionalities inconnection with the image processing. Thus, another type of media thatmay bear the software elements includes optical, electrical, andelectromagnetic waves, such as used across physical interfaces betweenlocal devices, through wired and optical landline networks and overvarious air-links. The physical elements that carry such waves, such aswired or wireless links, optical links or the like, also may beconsidered as media bearing the software. As used herein, unlessrestricted to tangible “storage” media, terms such as computer ormachine “readable medium” refer to any medium that participates inproviding instructions to a processor for execution.

A computer-readable medium may take many forms including, for example, atangible storage medium, a carrier wave medium, or physical transmissionmedium. Non-volatile storage media include, for example, optical ormagnetic disks, such as any of the storage devices in any computer(s) orthe like, which may be used to implement the system or any of itscomponents as shown in the drawings. Volatile storage media may includedynamic memory, such as a main memory of such a computer platform.Tangible transmission media may include coaxial cables; copper wire andfiber optics, including the wires that form a bus within a computersystem. Carrier-wave transmission media may take the form of electric orelectromagnetic signal, or acoustic or light waves such as thosegenerated during radio frequency (RF) and infrared (IR) datacommunications. Common forms of computer-readable media therefore mayinclude for example: a floppy disk, a flexible disk, a hard disk, amagnetic tape, any other magnetic medium, a CD-ROM, a DVD or DVD-ROM,any other optical medium, punch cards paper tape, any other physicalstorage medium with patterns of holes, a RAM, a PROM or an EPROM, aFLASH-EPROM, any other memory chip or cartridge, a carrier wavetransporting data or instructions, cables or links transporting such acarrier wave, or any other medium from which a computer may readprogramming code and/or data. Many of these forms of computer readablemedia may be involved in carrying one or more sequences of one or moreinstructions to a physical processor for execution.

The processor 320 may execute program instructions stored in a storagedevice (e.g., disk 370, ROM 330, RAM 340) to perform one or morefunctions of the processing engine 130 described in the presentdisclosure. The processor 320 may include a central processing unit(CPU), an application-specific integrated circuit (ASIC), anapplication-specific instruction-set processor (ASIP), a graphicsprocessing unit (GPU), a physics processing unit (PPU), a digital signalprocessor (DSP), a field programmable gate array (FPGA), a programmablelogic device (PLD), a microcontroller unit, an advanced RISC machinesprocessor (ARM), or the like, or a combination thereof.

The I/O 360 may input and/or output signals, data, information, etc. Insome embodiments, the I/O 360 may enable a user interaction with theprocessing engine 130. In some embodiments, the I/O 360 may include aninput device and an output device. Examples of the input device mayinclude a keyboard, a mouse, a touch screen, a microphone, or the like,or any combination thereof. Examples of the output device may include adisplay device, a loudspeaker, a printer, a projector, or the like, orany combination thereof. Examples of the display device may include aliquid crystal display (LCD), a light-emitting diode (LED)-baseddisplay, a flat panel display, a curved screen, a television device, acathode ray tube (CRT), a touch screen, or the like, or any combinationthereof.

The communication port 350 may be connected to a network (e.g., thenetwork 140) to facilitate data communications. The communication port350 may establish connections between the MR scanner 110, the examiningtable 120, the processing engine 130, the terminal device 160, and/orthe storage device 150. The connection may be a wired connection, awireless connection, any other communication connection that can enabledata transmission and/or reception, or any combination of theseconnections. The wired connection may include, for example, anelectrical cable, an optical cable, a telephone wire, or the like, orany combination thereof. The wireless connection may include, forexample, a Bluetooth™ link, a Wi-Fi™ link, a WiMax™ link, a WLAN link, aZigBee link, a mobile network link (e.g., 3G, 4G, 5G, etc.), or thelike, or any combination thereof. In some embodiments, the communicationport 350 may be and/or include a standardized communication port, suchas RS232, RS485, etc. In some embodiments, the communication port 350may be a specially designed communication port. For example, thecommunication port 350 may be designed in accordance with the digitalimaging and communications in medicine (DICOM) protocol.

Those skilled in the art will recognize that the present teachings areamenable to a variety of modifications and/or enhancements. For example,although the implementation of various components described herein maybe embodied in a hardware device, it may also be implemented as asoftware only solution, for example, an installation on an existingserver. In addition, the processing engine 130 as disclosed herein maybe implemented as a firmware, firmware/software combination,firmware/hardware combination, or a hardware/firmware/softwarecombination.

FIG. 4 is a schematic diagram illustrating exemplary hardware and/orsoftware components of an exemplary mobile device on which the terminaldevice 160 may be implemented according to some embodiments of thepresent disclosure. As illustrated in FIG. 4, the mobile device 400 mayinclude a communication platform 410, a display 420, a graphicprocessing unit (GPU) 430, a central processing unit (CPU) 440, an I/O450, a memory 460, and a storage 490. In some embodiments, any othersuitable component, including but not limited to a system bus or acontroller (not shown), may also be included in the mobile device 400.In some embodiments, a mobile operating system 470 (e.g., iOS™,Android™, Windows Phone™, etc.) and one or more applications 480 may beloaded into the memory 460 from the storage 490 in order to be executedby the CPU 440. The applications 480 may include a browser or any othersuitable mobile apps for receiving and rendering information respect todata processing or other information from the processing engine 130.User interactions with the information stream may be achieved via theI/O 450 and provided to the processing engine 130 and/or othercomponents of the imaging system 100 via the network 140.

To implement various modules, units, and their functionalities describedin the present disclosure, computer hardware platforms may be used asthe hardware platform(s) for one or more of the elements describedherein. A computer with user interface elements may be used to implementa personal computer (PC) or any other type of work station or externaldevice. A computer may also act as a server if appropriately programmed.

FIG. 5 is a block diagram illustrating an exemplary processing engineaccording to some embodiments of the present disclosure. The processingengine 130 may include an acquisition module 510, a control module 520,a storage module 530, and a processing module 540. In some embodiments,the acquisition module 510, the control module 520, the storage module530, and/or the processing module 540 may be connected to and/orcommunicate with each other via a wired connection, a wirelessconnection, or any combination thereof.

The acquisition module 510 may acquire data. In some embodiments, thedata may be acquired from the MR scanner 110, the examining table 120,the storage device 150, and/or the terminal device 160. In someembodiments, the data may include a scanning protocol, at least oneportion of imaging gradient parameters as described elsewhere in thepresent disclosure, image data (e.g., encoded MR signals), instructions,or the like, or any combination thereof. The instructions may beexecuted by the processor(s) of the processing engine 130 to performexemplary methods described in the present disclosure. In someembodiments, the acquired data may be transmitted the processing module540 for further processing, or stored in the storage module 530.

The control module 520 may control operations of the acquisition module510, the examining table 120, the storage module 530, and/or theprocessing module 540 (e.g., by generating one or more controlparameters). For example, the control module 520 may control theacquisition module 510 to acquire data. As another example, the controlmodule 520 may control the movement of the examining table 120. As stillanother example, the control module 520 may control the processingmodule 540 to process a scanning protocol for determining one or moreimaging gradient parameters. In some embodiments, the control module 520may receive a real-time command or retrieve a predetermined commandprovided by a user (e.g., a doctor) to control one or more operations ofthe acquisition module 510 and/or the processing module 540. Forexample, the control module 520 may adjust the acquisition module 510and/or the processing module 540 to generate image data associated withthe MR signals according to the real-time command and/or thepredetermined command. In some embodiments, the control module 520 maycommunicate with one or more other modules of the processing engine 130for exchanging information and/or data.

The storage module 530 may store imaging gradient parameters, processeddata, instructions, or the like, or any combination thereof. In someembodiments, the storage module 530 may store one or more scanningprotocols, portion of imaging gradient parameters and/or encoded MRsignals. In some embodiments, the storage module 530 may storeprogram(s) and/or instruction(s) that can be executed by theprocessor(s) of the processing engine 130 to acquire data, determineimaging gradient parameters, reconstruct an image based on the imaginggradient parameters, and/or display any intermediate result or aresultant image.

The processing module 540 may process data provided by various modulesof the processing engine 130. In some embodiments, the processing module540 may process MR signals for reconstructing an MR image acquired bythe acquisition module 510, retrieved from the storage module 530 and/orthe storage device 150, etc. In some embodiments, the processing module540 may determine and/or adjust at least one portion of imaging gradientparameters, such as a flow sensitive gradient based on other imaginggradient parameters.

In some embodiments, one or more modules illustrated in FIG. 5 may beimplemented in at least part of the exemplary imaging system 100 asillustrated in FIG. 1. For example, the acquisition module 510, thecontrol module 520, the storage module 530, and/or the processing module540 may be integrated into a console (not shown). Via the console, auser may set parameters for scanning a subject, controlling imagingprocesses, controlling parameters for reconstruction of an image,visualizing a virtual scene associated with the subject, etc. In someembodiments, the console may be implemented via the processing engine130 and/or the terminal device 160.

FIG. 6 is a block diagram illustrating an exemplary processing moduleaccording to some embodiments of the present disclosure. As shown, theprocessing module 540 may include an initialization unit 610, anadjustment unit 620, a judgment unit 630, and a determination unit 640.In some embodiments, the initialization unit 610, the adjustment unit620, the judgment unit 630, and/or the determination unit 640 may beconnected to and/or communicate with each other via a wired connection,a wireless connection, or any combination thereof.

The initialization unit 610 may set an initial value to one or moreimaging gradient parameters according to a scanning protocol. In someembodiments, the initialization unit 610 may initialize at least oneduration and at least one amplitude value of at least one flow sensitivegradient. For example, if the flow sensitive gradient block has two flowsensitive gradients, for example, a first flow sensitive gradient and asecond flow sensitive gradient, the initialization unit 610 mayinitialize a first duration t1 and a first amplitude value G1 of thefirst flow sensitive gradient, and a second duration t2 and a secondamplitude value G2 of the second flow sensitive gradient.

The adjustment unit 620 may adjust at least one parameter of the pulsesequence. For example, one or more flow sensitive gradient block may beadded to at least one imaging gradient direction (e.g., a phase encoding(PE) gradient, a readout (RO) gradient, a slice selecting encoding (SPE)gradient, etc.). Then, the imaging gradient parameter may be adjustedbased on the parameter of the flow sensitive gradient block. In someembodiments, one or more parameters (e.g., a duration, an amplitudevalue, etc.) of the flow sensitive gradient block may be adjusted in aprocess for determining the flow sensitive gradient block.

The judgment unit 630 may perform a judgment function in a process fordetermining a flow sensitive gradient block. In some embodiments, thejudgment unit 630 may determine that whether the flow sensitive gradientblock is in accordance with a target condition. For example, thejudgment unit 630 may determine that whether the zeroth-order gradientmoment or the first-order gradient moment associated with the flowsensitive gradient block is in accordance with a target value, such as“0”. As another example, the judgment unit 630 may determine thatwhether an amplitude value of a flow sensitive gradient is equal to orless than a threshold. In some embodiments, the target condition may bedetermined based on functions of the flow sensitive gradient block, suchas flow encoding, flow compensation, flow dephasing, etc.

The determination unit 640 may determine one or more parameters relatedto a flow sensitive gradient block. In some embodiments, the parametersrelated to the flow sensitive gradient block may be determined based onother imaging gradient parameters, such as the parameters related to thephase encoding (PE) gradient, the readout (RO) gradient, the sliceselecting encoding (SPE) gradient, etc.

This description is intended to be illustrative, and not to limit thescope of the present disclosure. Many alternatives, modifications, andvariations will be apparent to those skilled in the art. The features,structures, methods, and characteristics of the exemplary embodimentsdescribed herein may be combined in various ways to obtain additionaland/or alternative exemplary embodiments. For example, the adjustmentunit 620 and the determination unit 640 may be integrated into onesingle unit. However, those variations and modifications do not departthe scope of the present disclosure.

FIG. 7 is a flowchart illustrating an exemplary process for determininga flow sensitive gradient block according to some embodiments of thepresent disclosure. The process 700 may be executed by the imagingsystem 100. For example, the process 700 may be implemented as a set ofinstructions (e.g., an application) stored in storage device 150 and/orstorage module 530 in the processing engine 130. The processing engine130 may execute the set of instructions and may accordingly be directedto perform the process 700 in the imaging system 100.

In 702, the processing engine 130 may determine an imaging gradientparameter according to a scanning protocol. The scanning protocol may bedeveloped for various diseases and clinical scenarios. For example, thescanning protocol may be determined (or chosen) according to differentsubject or regions including head, brain, neck, body, shoulder, arm,thorax, cardiac, stomach, blood vessel, soft tissue, knee, feet, or thelike, or any combination thereof. As another example, the scanningprotocol may be an adult protocol, pediatric protocol, or animalprotocol, etc. In some embodiments, the scanning protocol may beassociated with a signal modality imaging device and/or amulti-modalities imaging device and include, for example, an MRIprotocol, a PET-MRI protocol, a PET-CT protocol, etc. In someembodiments, the scanning protocol may be a standard protocolpreinstalled in the imaging system 100. In some other embodiments, thescanning protocol may also be modified, revised, deleted, added, and/orupdated by a user. The scanning protocol may be stored in the storagedevice 150 and/or the processing engine 130.

In some embodiments, the scanning protocol may have features including,for example, a weighted imaging method, a pulse sequence mode, a slicethickness, an inter-slice gap, a field of view (FOV), a scanning range,or the like, or any combination thereof. The weighted imaging method maybe, for example, T1-weighted imaging (T1WI), T2-weighted imaging (T2WI),proton-density-weighted imaging (PDWI), T2*-weighted imaging (T2*WI),diffusion-weighted imaging (DWI), or the like, or any combinationthereof. The pulse sequence mode may include, for example, a freeinduction decay (FID) sequence, a spin echo (SE) sequence, a fast spinecho (FSE) sequence (or turbo spin echo (TSE) sequence, rapidacquisition with relaxation enhancement (RARE) sequence, etc.), aninversion recovery (IR) sequence, a gradient recalled echo (GRE)sequence, a fast imaging with steady-state precession (FISP) sequence,or the like, or any combination thereof. The slice thickness may be thethickness of an excitation slice including, for example, 1 micrometer, 2micrometers, 3 micrometers, or any other suitable values. Theinter-slice thickness may be the thickness of the gap between twoadjacent slices including, for example, 0 micrometer, 0.5 micrometer, 1micrometer, or any other suitable values. The FOV may be associated withthe area of the scanning captured, for example, 20 centimeters×20centimeters, 20 centimeters×30 centimeters, or any other suitablevalues. The scanning range may be a region of a subject to be scanned,for example, an entire brain, a half breast, a left arm, or the like, orany combination thereof.

In some embodiments, the pulse sequence determined by the scanningprotocol may include, for example, an RF pulse, an imaging gradientdirection, and an MR signal. The gradient field may include a sliceselecting gradient, a phase encoding gradient, and/or a readoutgradient. Merely by way of example, the pulse sequence may be describedas an exemplary diagram in FIG. 10-A. As illustrated in FIG. 10-A, thepulse sequence may include several components displayed in severalsequence axes. The sequence axes may include an RF pulse axis, a sliceselecting axis, a phase encoding axis, a readout axis, and ananalog-to-digital converter (ADC) axis (not shown). In some otherembodiments, the time sequence axes may be modified by, for example,adding an MR signal axis and/or deleting a phase encoding axis.

In some embodiments, the processing engine 130 may determine a parameterof the imaging gradient based on the scanning protocol. The parameter ofthe imaging gradient may include a repetition time (TR), an echo time(TE), a duration and/or an amplitude value of slice selecting gradientG_(rf), a duration and/or an amplitude value of a readout gradientG_(ro), or the like, or any combination thereof. For example, whenexcites a desired slice, a slice selecting gradient G_(rf) may beimposed along a direction perpendicular to the plane of the desiredslice simultaneously with the RF pulse. TE may be associated with timefrom the center of the RF pulse to the center of an echo. For pulsesequence with multi-echoes, several echo times may be defined and notedas TE₁, TE₂, TE₃, . . . , TE_(n), where n may be a positive integer.

In 704, the processing engine 130 may determine a time origin related tothe imaging gradient and a target condition for a flow sensitivegradient block associated with the time origin. The time origin may bezero time used for gradient moment calculation, for example, determininga zeroth-order gradient moment M0 and/or a first-order gradient momentM1 as described elsewhere in the present disclosure. In someembodiments, the time origin may be determined according to the centerof an echo. For example, as illustrated in FIG. 10-A, the center of anecho (e.g., TE₁, TE₂, TE₃, . . . , TE_(n)) may be selected as the timeorigin, and noted as t=0. When TE is selected as the time origin, everytime point before the center of the echo may have a negative value. Asanother example, any time point in the pulse sequence may be designatedas the time origin according to different scenarios. It should be notedthat the selection of the time origin does not affect the imaginggradient and the performance of the process 700 in the presentdisclosure.

In some embodiments, in 704, the processing engine 130 may alsodetermine a target condition for a flow sensitive gradient blockassociated with the time origin. The flow sensitive gradient block maybe a gradient portion added into the imaging gradient in the FIG. 10-Aand/or FIG. 11-A. As illustrated in FIG. 10-A and/or FIG. 11-A, agradient portion corresponding to a duration T before the readoutgradient in the pulse sequence may be used to design the flow sensitivegradient block. In some embodiments, the flow sensitive gradient blockmay include at least one flow sensitive gradient. The shape of the flowsensitive gradient may include an echelon, a rectangle, a square, anarch, an irregular shape, or the like, or any combination thereof.Merely by way of example, the flow sensitive gradient may have a shapeof echelon as shown in FIG. 10-B, FIG. 11-B, and FIG. 12.

In some embodiments, for a spin position r locating in a spin coordinatesystem having a center frequency consistent with a Larmor frequency. TheLarmor frequency may be associated with the main magnetic fieldstrength. In some embodiments, the spin position r may be a function oftime t described as:r(t)=r ₀ +vt  (1),where v represents a velocity assumed to be constant, and r₀ representsan initial position at the time origin (e.g., t=0).

In some embodiments, when imposed by the flow sensitive gradient havingan amplitude value of G by a time period 0-τ, the spin position r maygenerate a phase described as:φ(τ)=−γ∫₀ ^(τ) G(t)r(t)dt=−γr ₀∫₀ ^(τ) G(t)dt−γv∫ ₀ ^(τ) G(t)tdt  (2),where γ represents a gyromagnetic ratio.

In some embodiments, a zeroth-order (0th) moment M0 and a first order(1st) moment M1 of the flow sensitive gradient may be described as:M0=∫₀ ^(τ) G(t)dt  (3),M1=∫₀ ^(τ) G(t)tdt  (4).

In some embodiments, the determination of the target condition for theflow sensitive gradient block may include designating M0 and/or M1 asM_(0-target) and/or M_(1-target). Merely by way of example, the targetcondition may be M_(0-target)=0 and/or M_(1-arget)=0 at the time origin.

In 706, the processing engine 130 may determine a parameter of the flowsensitive gradient block according to the target condition. In someembodiments, the parameter of the flow sensitive gradient block mayinclude at least one duration and at least one amplitude value of the atleast one flow sensitive gradient. For example, if the flow sensitivegradient block has two flow sensitive gradients (e.g., a first flowsensitive gradient P1 and a second flow sensitive gradient P2 as shownin FIG. 10-B), the processing engine 130 may determine a first durationt1 and a first amplitude value G1 of the first flow sensitive gradient,as well as a second duration t2 and a second amplitude value G2 of thesecond flow sensitive gradient. In some embodiments, t1, t2, G1, and G2may be determined according to the target condition M_(0-target) and/orM_(1-target), based, for example, on the formula (3) and/or (4). In someembodiments, the sum of t1 and t2 may be equal to the duration T of theflow sensitive gradient block.

In some embodiments, in 706, the processing engine 130 may iterativelycalculate or compute the parameter of the flow sensitive gradient block.Merely by way of example, the parameter may be adjusted or changed oneor more times to match the target condition, as described in, forexample, FIG. 8 or 9 and the description thereof.

In 708, the processing engine 130 may adjust the imaging gradientparameter according to the parameter of the flow sensitive gradientblock. In some embodiments, when the parameter of the flow sensitivegradient block is determined, the parameter of the imaging gradient maybe adjusted accordingly. The parameter of the imaging gradient mayinclude, for example, a repetition time (TR), an echo time (TE), astarting time of slice selecting gradient G_(rf), a starting time of areadout gradient G_(ro). In some embodiments, the flow sensitivegradient block may be inserted into the pulse sequence to generate anadjusted pulse sequence as illustrated in FIG. 10-B and/or FIG. 11-B.

FIG. 8 is a flowchart illustrating an exemplary process for determininga flow sensitive gradient block according to some embodiments of thepresent disclosure. The process 800 may be executed by the imagingsystem 100. For example, the process 800 may be implemented as a set ofinstructions (e.g., an application) stored in storage device 150 and/orstorage module 530 in the processing engine 130. The processing engine130 may execute the set of instructions and may accordingly be directedto perform the process 800 in the imaging system 100.

In 802, the processing engine 130 may initialize a duration T and a timedifference ΔT associated with the flow sensitive gradient block. Asillustrated in 706, the duration T of the flow sensitive gradient blockmay be determined. In some embodiments, the duration T may be a value,for example, doubling a rise time of the imaging gradient. Then the timedifference ΔT associated with the flow sensitive gradient block may bedetermined accordingly. For example, the time difference ΔT may be adistance between the time origin (t=0) and a time point of the flowsensitive gradient block as shown in FIG. 10-A or FIG. 11-A. The timepoint may be at any position of the flow sensitive gradient block,merely by way of example, the time point may be an ending time.

In 804, the processing engine 130 may determine a target zeroth-ordergradient moment M_(0-target) and a target first-order gradient momentM_(1-target) associated with the flow sensitive gradient block. In someembodiments, as shown in FIG. 10-B and/or FIG. 11-B, the targetzeroth-order gradient moment M_(0-target) and the target first-ordergradient moment M_(1-target) associated with the slice selecting axis,the phase encoding axis, and the readout axis may be the same ordifferent. Merely by way of example, in the slice selecting axis, thetarget zeroth-order gradient moment M_(0-target) may be the sum ofzeroth-order gradient moment associated with a rephrase gradient of theslice selecting gradient G_(rf) and zeroth-order gradient momentdemanded by a present slice selecting phase encoding steps. The targetfirst-order gradient moment M_(1-target) may be a negative value offirst-order gradient moment among TE₁ associated with the sliceselecting gradient G_(rf) from the center of the RF pulse to the endingtime of the slice selecting gradient G_(rf). As another example, in thephase encoding axis, the target zeroth-order gradient momentM_(0-target) may be zeroth-order gradient moment demanded by presentphase encoding steps. The target first-order gradient momentM_(1-target) may be zero. As still another example, in the readout axis,the target zeroth-order gradient moment M_(0-target) may be zeroth-ordergradient moment associated with a prephrase gradient of the readoutgradient G_(ro). For example, the target zeroth-order gradient momentM_(0-target) may be a negative value of zeroth-order gradient momentamong TE₁ of the readout gradient G_(ro) before TE₁. The targetfirst-order gradient moment M_(1-target) may be a negative value offirst-order gradient moment among TE₁ of the readout gradient G_(ro)before TE₁.

In some embodiments, a moment higher than the second order (e.g., M2,M3, M4, . . . , etc.) of the imaging gradient may be used to perform theprocess 800 according to the present disclosure.

In 806, the processing engine 130 may determine a parameter of the flowsensitive gradient block according to the M_(0-target) and M_(1-target).In some embodiments, the parameter of the flow sensitive gradient blockmay include at least one duration and at least one amplitude value ofthe at least one flow sensitive gradient. Merely by way of, as shown inFIG. 10-B, if the flow sensitive gradient block has two flow sensitivegradients (e.g., a first flow sensitive gradient P1 and a second flowsensitive gradient P2 on the SPE axis, the PE axis, and/or the RO axis),the processing engine 130 may determine a first duration t1 and a firstamplitude value G1 of the first flow sensitive gradient, a secondduration t2 and a second amplitude value G2 of the second flow sensitivegradient.

In some embodiments, the sum of t1 and t2 may be equal to the duration Tof the flow sensitive gradient block. Given the duration T of the flowsensitive gradient block is stationary, t1 and t2 may be adjusteddynamically. In some embodiments, when at least one pair of t1 and t2meet the demand target condition (e.g., M_(0-target) and M_(1-target))is required, the processing engine 130 may determine the first amplitudevalue G1 of the first flow sensitive gradient, the second amplitudevalue G2 of the second flow sensitive gradient, based on the formula (3)and/or (4).

In 808, the processing engine 130 may determine whether the amplitudevalue of the flow sensitive gradient is equal to or less than athreshold. In some embodiments, the threshold may be a value, a range, aformula, an order, or the like, or any combination thereof. Merely byway of example, the threshold may be associated with a maximum gradientof the imaging system 100. If the amplitude value of the flow sensitivegradient (e.g., G1, G2, etc.) is equal to or less than the threshold,the process 800 may proceed to 810. If the amplitude value of the flowsensitive gradient (e.g., G1, G2, etc.) is greater than the threshold,the process 800 may proceed to 812.

In 812, the processing engine 130 may adjust the duration T. Merely byway of example, the processing engine 130 may increase or decrease theduration T by using an adjusting value. For example, the duration T maybe increased by the adjusting value to generate an adjusted duration T.As another example, the duration T may be changed by multiplying anadjusting coefficient including, for example, 0.6, 0.8, 1.0, 1.2, 1.4, .. . , etc.

After 812, the process may proceed to 804 to determine a targetzeroth-order gradient moment M_(0-target) and a target first-ordergradient moment M_(1-target) associated with the flow sensitive gradientblock. In some embodiments, when the duration T is adjusted, the echotime TE (e.g., TE₁, TE₂, TE₃, . . . , TE_(n)) may be changedaccordingly. Thus the target zeroth-order gradient moment M_(0-target)and the target first moment M_(1-target) may be re-determined based onthe echo time TE (e.g., TE₁, TE₂, TE₃, . . . , TE_(n)).

In 810, the processing engine 130 may determine the duration T as afinal duration T′ (or a shared duration T′) of the flow sensitivegradient block. In some embodiments, the process 800 may be executed onthe slice selecting axis, the phase encoding axis, and the readout axisindependently. For example, the processing engine 130 may determine afinal duration Ts' (or an optimal duration Ts′) associated with sliceselecting axis, a final duration Tp′ (or an optimal duration Tp′)associated with the phase encoding axis, and a final duration Tr′ (or anoptimal duration Tr′) associated with the readout coordinate axis. Insome embodiments, the processing engine 130 may select a maximum of Tr′,Tp′, and Ts' as the final duration T′ (or the shared duration T′).

In some embodiments, when the final duration T′ (the shared duration T′)is determined in 810, the parameter of the imaging gradient including,for example, a repetition time (TR), an echo time (TE), a staring timeof slice selecting gradient G_(rf), a starting time of a readoutgradient G_(ro) may be adjusted accordingly. In some embodiments, theflow sensitive gradient block (t1, G1, t2, G2) may be inserted into thepulse sequence to generate an adjusted pulse sequence as illustrated inFIG. 10-B.

In some embodiments, the flow sensitive gradient block may be bipolar,for example, including at least two flow sensitive gradients associatedwith a double-pulse field gradient, G1=−G2. In some embodiments, theflow sensitive gradient block may be monopolar, for example, includingone flow sensitive gradient associated with a single-pulse fieldgradient, G1=G, t1=T, G2=0, and t2=0. The embodiments may also beperformed by process 800 as described in FIG. 10-A and FIG. 10-B in thepresent disclosure.

In some embodiments, the processing engine 130 may determine a flowsensitive gradient block as illustrated in FIG. 11-A and FIG. 11-B. Asshown in FIG. 10-A, the pulse sequence may include two echoes, forexample, a first echo and a second echo. In some embodiments, there maybe a first flow sensitive gradient block associated with the first echoand a second flow sensitive gradient block associated with the secondecho. The first flow sensitive gradient block and/or the second flowsensitive gradient block may be determined according to the process 700or 800. For example, the processing engine 130 may determine the firstflow sensitive gradient block according to the description elsewhere inthe FIGS. 10-A and 10-B.

As another example, the processing engine 130 may determine the secondflow sensitive gradient block based on the first flow sensitive gradientblock. In some embodiments, a new readout gradient G_(ro)′ may beinserted according to the first flow sensitive gradient block. Forexample, G_(ro)′ may have a consistent direction with G_(ro), which canbe called a monopolar readout mode. As another example, G_(ro)′ may havean opposite direction compared with G_(ro), which can be called abipolar readout mode. The processing engine 130 may re-determine theecho time of the second echo TE₂ as a new time origin, and the durationT of the second flow sensitive gradient block. In some embodiments, theduration T may be a value, for example, doubling a rise time of theimaging gradient. Then the time difference ΔT associated with the secondflow sensitive gradient block may be determined accordingly. Forexample, the time difference ΔT may be a distance between the new timeorigin (t=0) and a time point (e.g., an ending time) of the second flowsensitive gradient block (or a starting time of the new readout gradientG_(ro)′) as shown in FIG. 11-A or FIG. 11-B.

The processing engine 130 may determine a target zeroth-order gradientmoment M_(0-target) and a target first-order gradient momentM_(1-target) associated with the second flow sensitive gradient block.In some embodiments, the target zeroth-order gradient momentM_(0-target) and the target first-order gradient moment M_(1-target)associated with the slice selecting axis, the phase encoding axis, andthe readout axis may be the same or different. Merely by way of example,as shown in FIG. 11-A, in the slice selecting axis and/or phase encodingaxis, the target zeroth-order gradient moment M_(0-target) may be zero.The target first-order gradient moment M_(1-target) may be a negativevalue of first-order gradient moment among TE₂ associated with flowsensitive gradient G1, G2, and/or readout gradient G_(ro) before thecenter of the second echo. As still another example, in the readoutaxis, the target zeroth-order gradient moment M_(0-target) may be may bea negative value of the sum of zeroth-order gradient moment of thereadout gradient G_(ro) and the new readout gradient G_(ro)′ between TE₁and TE₂. The target first-order gradient moment M_(1-target) may be anegative value of first-order gradient moment among TE₂ of the readoutgradient G_(ro) and/or the new readout gradient G_(ro)′ between TE₁ andTE₂.

In some embodiments, a moment more than second order (e.g., M2, M3, M4,. . . , etc.) of the imaging gradient and/or the flow sensitive gradientmay be used to determine the flow sensitive gradient block.

In some embodiments, the processing engine 130 may determine a parameterof the second flow sensitive gradient block including, for example, atleast one duration and at least one amplitude value of the at least oneflow sensitive gradient. Merely by way of, as shown in FIG. 11-B, if thesecond flow sensitive gradient block has two flow sensitive gradients(e.g., a first flow sensitive gradient P1 and a second flow sensitivegradient P2 on the SPE axis, the PE axis, and/or the RO(bi) axis), theprocessing engine 130 may determine a first duration t1 and a firstamplitude value G1 of the first flow sensitive gradient, as well as asecond duration t2 and a second amplitude value G2 of the second flowsensitive gradient.

In some embodiments, the sum of t1 and t2 may be equal to the duration Tof the flow sensitive gradient block. Given the duration T of the flowsensitive gradient block is fixed, t1 and t2 may be adjusteddynamically. In some embodiments, when at least one pair of t1 and t2meet the demand target condition (e.g., M_(0-target) and M_(1-target))is required, the processing engine 130 may determine the first amplitudevalue G1 of the first flow sensitive gradient, the second amplitudevalue G2 of the second flow sensitive gradient, based on the formula (3)and/or (4).

In some embodiments, the processing engine 130 may determine whether theamplitude value of the flow sensitive gradient is equal to or less thana threshold. In some embodiments, the threshold may be a value, a range,a formula, an order, or the like, or any combination thereof. Merely byway of example, the threshold may be associated with the maximumgradient of the imaging system 100. If the amplitude value of the flowsensitive gradient (e.g., G1, G2, etc.) is equal to or less than thethreshold, the processing engine 130 may determine the duration T as afinal duration T′ of the second flow sensitive gradient block. If theamplitude value of the flow sensitive gradient (e.g., G1, G2, etc.) isgreater than the threshold, the processing engine 130 may adjust theduration T. Merely by way of example, the processing engine 130 mayincrease or decrease the duration T by using an adjusting value. Forexample, the duration T may be increased by the adjusting value togenerate an adjusted duration T. As another example, the duration T maybe changed by multiplying an adjusting coefficient including, forexample, 0.6, 0.8, 1.0, 1.2, 1.4, . . . , etc. In some embodiments, whenthe duration T is adjusted, the echo time TE (e.g., TE₁, TE₂, TE₃, . . ., TE_(n)) may be changed accordingly. Thus the target zeroth-ordergradient moment M_(0-target) and the target first-order gradient momentM_(1-target) may be re-determined based on the changed or updated echotime TE (e.g., TE₁, TE₂, TE₃, . . . , TE_(n)).

In some embodiments, the second flow sensitive gradient block may beexecuted on the slice selecting axis, the phase encoding axis, and thereadout axis independently as shown in FIG. 11-A or FIG. 11-B. Forexample, the processing engine 130 may determine a final duration Ts'(or an optimal duration Ts′) associated with slice selecting axis, afinal duration Tp′ (or an optimal Tp′) associated with the phaseencoding axis, and a final duration Tr′ (or an optimal duration Tr′)associated with the readout coordinate axis. In some embodiments, theprocessing engine 130 may select the greatest duration among Tr′, Tp′,and Ts' as the final duration T′ (or the shared duration T′).

In some embodiments, when the final duration T′ (or the shared durationT′) is determined, the parameter of the imaging gradient including, forexample, a repetition time (TR), an echo time (TE₂), and a starting timeof a readout gradient G_(ro)′ may be adjusted accordingly. In someembodiments, the second flow sensitive gradient block (t1, G1, t2, G2)may be inserted into the pulse sequence to generate an adjusted pulsesequence as illustrated in FIG. 11-B.

FIG. 9 is a flowchart illustrating an exemplary process for determininga flow sensitive gradient block according to some embodiments of thepresent disclosure. The process 900 may be executed by the imagingsystem 100. For example, the process 900 may be implemented as a set ofinstructions (e.g., an application) stored in storage device 150 and/orstorage module 530 in the processing engine 130. The processing engine130 may execute the set of instructions and may accordingly be directedto perform the process 900 in the imaging system 100.

In 902, the processing engine 130 may obtain a parameter of a flowsensitive gradient block. The parameter may include a duration T, a timedifference ΔT, a target zeroth-order gradient moment M_(0-target), and atarget first-order gradient moment M_(1-target) associated with a flowsensitive gradient block. In some embodiments, T, ΔT, M_(0-target), andM_(1-target) may be determined according to the description of step 802and/or 804 in FIG. 8.

In 904, the processing engine 130 may initialize a parameter of the flowsensitive gradient block. In some embodiments, the processing engine 130may initialize the amplitude value of the flow sensitive gradient blockto be a normalized value. In some embodiments, the normalized value maybe 1 or −1. For example, if the flow sensitive gradient block isbipolar, then the amplitude value G1 of the first flow sensitivegradient may be initialized to be 1 and the amplitude value G2 of thesecond flow sensitive gradient may be initialized to be −1. As anotherexample, if the flow compensating module is monopolar, then G1 may beinitialized to be 1 and G2 may be initialized to be zero, or G1 may beinitialized to be zero and G2 may be initialized to be 1. In someembodiments, a first duration t1 of the first sensitive gradient and asecond duration t2 of the second flow sensitive gradient may beinitialized so that t1=0 and t2=T.

In 906, the processing engine 130 may initialize two error tolerancethresholds ε1 and ε2 according to M_(1-target). For example, the errortolerance thresholds ε1 and ε2 may be set as values no more than10^(−N), where N may be an integer.

In 908, the processing engine 130 may determine a present M0 and apresent M1 based on the initialized t1, t2, G1, and G2. In someembodiments, the present M0 and the present M1 may be determinedaccording to the formula (3) and/or (4) as described in connection withstep 704 in FIG. 7.

In 910, the processing engine 130 may determine whether the targetfirst-order gradient moment M_(1-target) is equal to zero. IfM_(1-target) is equal to zero, the process 900 may proceed to 912. IfM_(1-target) is unequal to zero, the process 900 may proceed to 914.

In 912, the processing engine 130 may determine whether the absolutevalue of the present M1 is less than the error tolerance threshold ε1.If the absolute value of the present M1 is less than the error tolerancethreshold ε1, the process 900 may proceed to 918. If the absolute valueof the present M1 is not less than the error tolerance threshold ε1, theprocess 900 may proceed to 916.

In 914, the processing engine 130 may judge whether the differencebetween the relative ratio of the present M1 and the present M0 and therelative ratio of M_(1-target) and M_(0-target) (also referred to as

$\left. {{\frac{M\; 1}{M\; 0} - \frac{M_{1\text{-}{target}}}{M_{0\text{-}{target}}}}} \right)$is less than the error tolerance threshold ε2. If the difference betweenthe relative ratio of M1 and M0 and the relative ratio of M_(1-target)and M_(0-target) is less than the error tolerance threshold ε2, theprocess and/or method 900 may proceed to 918. If the difference betweenthe relative ratio of M1 and M0 and the relative ratio of M_(1-target)and M_(0-target) is not less than the error tolerance threshold ε2, theprocess 900 may proceed to 916.

In 916, the processing engine 130 may adjust the duration t1 and t2. Forexample, the processing engine 130 may increase the duration t1 anddecrease the duration t2 by a step length h. The adjusted t1 and t2 maystill satisfy one or more restriction conditions. In some embodiments,the restriction conditions may include the sum of t1 and t2 is equal toT, t1 and t2 are both non-negative, and t1 and t2 are both no more thanT. In some embodiments, the value of step length h may be determinedpre-hand. For example, the step length h may be a value no more than10^(−N), where N may be an integer. In some embodiments, the step lengthh may be fixed, or may be varying during each iteration.

In 918, the processing engine 130 may determine t1 and t2. In someembodiments, t1 and t2 in 918 may be the same as the initialized t1 andt2 in 904. In some embodiments, t1 and t2 in 918 may be different fromthe initialized t1 and t2 (e.g., t1 and t2 adjusted in 916).

In 920, the processing engine 130 may determine G1 and G2 according toT, ΔT, t1, t2, M_(1-target) and M_(0-target) according to the formula(3) and/or (4).

FIG. 10-A illustrates exemplary diagrams of a single echo pulse sequenceaccording to some embodiment of the present disclosure. As shown in FIG.10-A, the signal echo pulse sequence may include several componentsdisplayed in several sequence axes. The sequence axes may include an RFpulse axis, a slice selecting (SPE) axis, a phase encoding (PE) axis,and a readout (RO) axis, and an analog-to-digital converter (ADC) axis(not shown). A slice selecting gradient G_(rf) and a readout gradientG_(ro) may be inserted onto the SPE axis and the RO axis respectively. Aflow sensitive gradient block may be inserted to the single echo pulsesequence. The flow sensitive gradient block may be used to perform afunction of flow compensation, flow encoding, and/or flow dephasing. Theduration T of the flow sensitive gradient block may be initialized to bea value. For example, the initial value of T may be chosen as twice therising time of least imaging gradient of the imaging system 100. Thecenter of an echo TE₁ (also referred to as echo time) may be selected asthe time origin and noted as t=0. The center of the echo TE₁ may bedetermined based on the duration T of the flow sensitive gradient block.The time difference ΔT starting from the starting time of G_(ro) whileending at TE₁ may be a fixed value, for example, the time difference ΔTmay be the half-width of the readout gradient G_(ro).

FIG. 10-B illustrates exemplary diagrams of a single echo pulse sequencewith the flow sensitive gradient block according to some embodiment ofthe present disclosure. As shown in FIG. 10-B, the SPE axis, the PEaxis, and the RO axis are respectively inserted by a flow sensitivegradient block. The flow sensitive gradient block may be bipolar on eachaxis, for example, including a first sensitive gradient P1 and a secondsensitive gradient P2. The parameters (e.g., the amplitude value G1 andthe duration t1 of the first flow sensitive gradient P1 and theamplitude value G2 and the duration t2 of the second flow sensitivegradient P2) of the flow sensitive gradient block on each axis may bedetermined based on the target zeroth-order gradient moment M_(0-target)and the target first-order gradient moment M_(1-target) at the timeorigin along the SPE axis, PE axis, and RO axis.

The target zeroth-order gradient moment M_(0-target) and the targetfirst-order gradient moment M_(1-target) for the flow sensitive gradientblock at the time origin along the SPE axis, PE axis, and RO axis may becalculated respectively. In the SPE axis, the target zeroth-ordergradient moment M_(0-target) may be the sum of zeroth-order gradientmoment associated with a rephrase gradient of the slice selectinggradient G_(rf) and zeroth-order gradient moment demanded by a presentslice selecting phase encoding steps. The target first-order gradientmoment M_(1-target) may be the negative value of first-order gradientmoment among TE₁ associated with the slice selecting gradient G_(rf)from the center of the RF pulse to the ending time of the sliceselecting gradient G_(rf). In the PE axis, the target zeroth-ordergradient moment M_(0-target) may be zeroth-order gradient momentdemanded by present phase encoding steps. The target first-ordergradient moment M_(1-target) may be zero. In the RO axis, the targetzeroth-order gradient moment M_(0-target) is a negative value ofzeroth-order gradient moment among TE₁ of the readout gradient G_(ro)before TE₁. The target first-order gradient moment M_(1-target) is anegative value of first-order gradient moment among TE₁ of the readoutgradient G_(ro) before TE₁.

A minimum value Ts' associated with the SPE axis, a minimum value Tp′associated with the PE axis, and a minimum value Tr′ associated with theRO axis may be determined independently according to the description asillustrated in FIG. 8. For each axis, in order to satisfy targetzeroth-order gradient moment M_(0-target) and target first-ordergradient moment M_(1-target), a smaller value of duration T may lead toa greater amplitude value of the flow sensitive gradient, which mayexceed the maximum value of the amplitude value allowed by the imagingsystem 100. On the SPE axis, the duration T may be increased todetermine a minimum value Ts' under which the amplitude value of theflow sensitive gradient is less than the maximum amplitude value that isallowed by the imaging system 100. Likewise, the minimum value Tp′associated with the PE axis and the minimum value Tr′ associated withthe RO axis may be determined. The amplitude values of the flowsensitive gradient along the PE axis and the RO axis may be less thanthe maximum amplitude value that is allowed by the imaging system 100.

Then a maximum of Tr′, Tp′, and Ts' may be defined as the final durationT′ (or the shared duration T′) for the PE axis, the RO axis, and the ROaxis. For the final duration T′, the amplitude value of the flowsensitive gradient may be calculated according to the description asillustrated in FIG. 9. The amplitude value of the flow sensitivegradient may meet the requirement for the target zeroth-order gradientmoment M_(0-target) and the target first-order gradient momentM_(1-target) along the SPE axis, PE axis, and RO axis.

FIG. 10-C illustrates exemplary diagrams of curves respecting tozeroth-order gradient moment M0 and first-order gradient moment M1varied with time according to some embodiment of the present disclosure.As shown in FIG. 10-C, the zeroth-order gradient moment M0 andfirst-order gradient moment M1 may have been normalized for the purposeof analysis. At TE₁, on the SPE axis and the PE axis, the first-ordergradient moment M1 may be zero, whereas the zeroth-order gradient momentM0 is the corresponding zeroth-order gradient moment demanded by presentphase encoding steps on the SPE axis and the PE axis respectively. Onthe RO axis, the zeroth-order gradient moment M0 and the first-ordergradient moment M1 are both zero at TE₁.

FIG. 11-A illustrates exemplary diagrams of a double echo pulse sequenceaccording to some embodiments of the present disclosure. As shown inFIG. 11-A, the double echo pulse sequence may include several componentsdisplayed in several time sequence axes. The sequence axes may includean RF pulse axis, a slice selecting (SPE) axis, a phase encoding (PE)axis, a readout (RO) axis, and an analog-to-digital converter (ADC) axis(not shown). The double echo pulse sequence may include two flowsensitive gradient blocks, e.g., a first flow sensitive gradient and asecond flow sensitive gradient. The first flow sensitive gradient blocksmay be determined as described herein in connection with FIG. 10-A toFIG. 10-C. To determine the second flow sensitive gradient, a sliceselecting gradient G_(rf) and a readout gradient G_(ro) may be insertedto the SPE axis and the RO axis respectively. In some embodiments, thereadout gradient G_(ro) may be associated with the feature of the firstflow sensitive gradient block. For example, if the readout is in amonopolar mode, the new readout gradient G_(ro)′ may have a consistentdirection with G_(ro), as shown in RO(mono) axis of FIG. 11-A. Asanother example, if the readout is in a bipolar mode, the new readoutgradient G_(ro)′ may have an opposite direction compared with G_(ro), asshown in RO(bi) axis of FIG. 11-A. The flow sensitive gradient block maybe used to perform a function of flow compensation, flow encoding,and/or flow dephasing. The duration T of the flow sensitive gradientblock may be initialized to be a value. For example, the initial valueof T may be chosen as twice the rising time of least imaging gradient ofthe imaging system 100. The center of an echo TE₂ may be selected as thetime origin, and noted as t=0. The time difference ΔT starting from thestarting time of G_(ro) while ending at TE₂ may be a fixed value, forexample, the time difference ΔT may be the half-width of the readoutgradient G_(ro).

FIG. 11-B illustrates exemplary diagrams of a double echo pulse sequencewith the flow sensitive gradient block according to some embodiment ofthe present disclosure. As shown in FIG. 11-B, the SPE axis, the PEaxis, and the RO axis are inserted by the second flow sensitive gradientblock. In some embodiments, the second flow sensitive gradient block maybe bipolar on each axis including, for example, a first flow sensitivegradient P1 and a second flow sensitive gradient P2. In someembodiments, the second flow sensitive gradient block may be monopolaron the RO axis, for example, including only one flow sensitive gradient.The parameters (e.g., the amplitude value G1 and the duration t1 of thefirst flow sensitive gradient P1 and the amplitude value G2 and theduration t2 of the second flow sensitive gradient P2) of the flowsensitive gradient block on each axis may be determined based on thetarget zeroth-order gradient moment M_(0-target) and the targetfirst-order gradient moment M_(1-target) at the time origin along theSPE axis, PE axis, and RO axis.

The target zeroth-order gradient moment M_(0-target) and the targetfirst-order gradient moment M_(1-target) for the flow sensitive gradientblock at the time origin along the SPE axis, PE axis, and RO axis may becalculated respectively. In the slice selecting axis and/or phaseencoding axis, the target zeroth-order gradient moment M_(0-target) maybe zero. The target first-order gradient moment M_(1-target) may be anegative value of first-order gradient moment among TE₂ associated withflow sensitive gradient G1, G2, and/or readout gradient G_(ro) beforethe center of the second echo. As still another example, in the readoutaxis, the target zeroth-order gradient moment M_(0-target) may be anegative value of sum of zeroth-order gradient moment of the readoutgradient G_(ro) and the new readout gradient G_(ro)′ between TE₁ andTE₂. The target first-order gradient moment M_(1-target) may be anegative value of first-order gradient moment among TE₂ of the readoutgradient G_(ro) and/or the new readout gradient G_(ro)′ between TE₁ andTE₂.

A minimum value Ts' associated with the SPE axis, a minimum value Tp′associated with the PE axis, and a minimum value Tr′ associated with theRO axis may be determined independently according to the description asillustrated in FIG. 8. For each axis, a smaller value of duration T maylead to a greater amplitude value of the flow sensitive gradient, whichmay exceed the maximum value of the amplitude value allowed by theimaging system 100. On the SPE axis, the duration T may be increased todetermine a minimum value Ts' under which the amplitude value of theflow sensitive gradient is less than the maximum amplitude value that isallowed by the imaging system 100. Likewise, the minimum value Tp′associated with the PE axis and the minimum value Tr′ associated withthe RO axis may be determined. The amplitude values of the flowsensitive gradient along the PE axis and the RO axis may be less thanthe maximum amplitude value that is allowed by the imaging system 100.

Then a maximum of Tr′, Tp′, and Ts' may be defined as the final durationT′ (or the shared duration T′) for the PE axis, the RO axis, and the ROaxis. For the final duration T′, the amplitude value of the flowsensitive gradient may be calculated according to the description asillustrated in FIG. 9. For example, a pair of t1 and t2 associated witha flow sensitive gradient block for each axis may be determinedaccording to the final duration T′. Then, the first amplitude value G1and the second amplitude value G2 of the flow sensitive gradient blockfor each axis may be determined based on the formula (3) and/or (4). Theamplitude values G1 and G2 of the flow sensitive gradient block for eachaxis may keep the zeroth-order gradient moment and the first-ordergradient moment of the flow sensitive gradient block for each axis inaccordance with the target zeroth-order gradient moment M_(0-target) andthe target first-order gradient moment M_(1-target) along the SPE axis,PE axis, and RO axis.

FIG. 11-C illustrates exemplary diagrams of curves respecting tozeroth-order gradient moment M0 and first-order gradient moment M1,which may vary with time according to some embodiments of the presentdisclosure. As shown in FIG. 11-C, the zeroth-order gradient moment M0and first-order gradient moment M1 may have been normalized. At TE₂, onthe SPE axis and the PE axis, their first-order gradient moment M1 areboth zero. On the RO axis, the zeroth-order gradient moment M0 and thefirst-order gradient moment M1 are both zero at TE₂. In someembodiments, for the monopolar readout mode, its corresponding flowsensitive gradient block may be monopolar (as described in RO(mono-1)axis) and/or bipolar (as described in RO(mono-2) axis).

FIG. 12-A illustrates exemplary diagrams of a multi-echoes sequencesaccording to some embodiments of the present disclosure. For example,the multi-echoes may include no less than three echoes (e.g., fiveechoes) as shown in FIG. 12-A. Each flow sensitive gradient blockcorresponding to each echo may be determined based on the process 800and process 900 as described elsewhere in the present disclosure. Merelyby way of example, a fifth flow sensitive gradient block associated withthe fifth echo in FIG. 12-A may be described as below.

As shown in FIG. 12-B, the time origin for determining the fifth flowsensitive gradient may be TE₅. On the SPE axis and the PE axis, thefirst-order gradient moment M1 at TE₅ may be equal to zero, and thefirst-order gradient moment M1 on each TE before TE₅ may not be equal tozero. In the RO axis, the zeroth-order gradient moment M0 andfirst-order gradient moment M1 at each TE may be equal to zero. In someembodiments, for the monopolar readout mode, its corresponding flowsensitive gradient block may be monopolar (as described in RO(mono-1)axis) and/or bipolar (as described in RO(mono-2) axis).

Having thus described the basic concepts, it may be rather apparent tothose skilled in the art after reading this detailed disclosure that theforegoing detailed disclosure is intended to be presented by way ofexample only and is not limiting. Various alterations, improvements, andmodifications may occur and are intended to those skilled in the art,though not expressly stated herein. These alterations, improvements, andmodifications are intended to be suggested by the present disclosure,and are within the spirit and scope of the exemplary embodiments of thepresent disclosure.

Moreover, certain terminology has been used to describe embodiments ofthe present disclosure. For example, the terms “one embodiment,” “anembodiment,” and/or “some embodiments” mean that a particular feature,structure or characteristic described in connection with the embodimentis included in at least one embodiment of the present disclosure.Therefore, it is emphasized and should be appreciated that two or morereferences to “an embodiment” or “one embodiment” or “an alternativeembodiment” in various portions of this specification are notnecessarily all referring to the same embodiment. Furthermore, theparticular features, structures or characteristics may be combined assuitable in one or more embodiments of the present disclosure.

Further, it will be appreciated by one skilled in the art, aspects ofthe present disclosure may be illustrated and described herein in any ofa number of patentable classes or context including any new and usefulprocess, machine, manufacture, or composition of matter, or any new anduseful improvement thereof. Accordingly, aspects of the presentdisclosure may be implemented entirely hardware, entirely software(including firmware, resident software, micro-code, etc.) or combiningsoftware and hardware implementation that may all generally be referredto herein as a “unit,” “module,” or “system.” Furthermore, aspects ofthe present disclosure may take the form of a computer program productembodied in one or more computer readable media having computer readableprogram code embodied thereon.

A computer readable signal medium may include a propagated data signalwith computer readable program code embodied therein, for example, inbaseband or as part of a carrier wave. Such a propagated signal may takeany of a variety of forms, including electro-magnetic, optical, or thelike, or any suitable combination thereof. A computer readable signalmedium may be any computer readable medium that is not a computerreadable storage medium and that may communicate, propagate, ortransport a program for use by or in connection with an instructionexecution system, apparatus, or device. Program code embodied on acomputer readable signal medium may be transmitted using any appropriatemedium, including wireless, wireline, optical fiber cable, RF, or thelike, or any suitable combination of the foregoing.

Computer program code for carrying out operations for aspects of thepresent disclosure may be written in any combination of one or moreprogramming languages, including an object oriented programming languagesuch as JAVA, SCALA, SMALLTALK, EIFFEL, JADE, EMERALD, C++, C#, VB. NET,PYTHON or the like, conventional procedural programming languages, suchas the “C” programming language, VISUAL BASIC, FORTRAN 2013, PERL, COBOL2012, PHP, ABAP, dynamic programming languages such as PYTHON, RUBY andBROOVY, or other programming languages. The program code may executeentirely on the user's computer, partly on the user's computer, as astand-alone software package, partly on the user's computer and partlyon a remote computer or entirely on the remote computer or server. Inthe latter scenario, the remote computer may be connected to the user'scomputer through any type of network, including a local area network(LAN) or a wide area network (WAN), or the connection may be made to anexternal computer (for example, through the Internet using an InternetService Provider) or in a cloud computing environment or offered as aservice such as a Software as a Service (SaaS).

Furthermore, the recited order of processing elements or sequences, orthe use of numbers, letters, or other designations therefore, is notintended to limit the claimed processes and methods to any order exceptas may be specified in the claims. Although the above disclosurediscusses through various examples what is currently considered to be avariety of useful embodiments of the disclosure, it is to be understoodthat such detail is solely for that purpose, and that the appendedclaims are not limited to the disclosed embodiments, but, on thecontrary, are intended to cover modifications and equivalentarrangements that are within the spirit and scope of the disclosedembodiments. For example, although the implementation of variouscomponents described above may be embodied in a hardware device, it mayalso be implemented as a software only solution, for example, aninstallation on an existing server or mobile device.

Similarly, it should be appreciated that in the foregoing description ofembodiments of the present disclosure, various features are sometimesgrouped together in a single embodiment, figure, or description thereoffor the purpose of streamlining the disclosure aiding in theunderstanding of one or more of the various inventive embodiments. Thismethod of disclosure, however, is not to be interpreted as reflecting anintention that the claimed subject matter requires more features thanare expressly recited in each claim. Rather, inventive embodiments liein less than all features of a single foregoing disclosed embodiment.

In some embodiments, the numbers expressing quantities or propertiesused to describe and claim certain embodiments of the application are tobe understood as being modified in some instances by the term “about,”“approximate,” or “substantially.” For example, “about,” “approximate,”or “substantially” may indicate ±20% variation of the value itdescribes, unless otherwise stated. Accordingly, in some embodiments,the numerical parameters set forth in the written description andattached claims are approximations that may vary depending upon thedesired properties sought to be obtained by a particular embodiment. Insome embodiments, the numerical parameters should be construed in lightof the number of reported significant digits and by applying ordinaryrounding techniques. Notwithstanding that the numerical ranges andparameters setting forth the broad scope of some embodiments of theapplication are approximations, the numerical values set forth in thespecific examples are reported as precisely as practicable.

Each of the patents, patent applications, publications of patentapplications, and other material, such as articles, books,specifications, publications, documents, things, and/or the like,referenced herein is hereby incorporated herein by this reference in itsentirety for all purposes, excepting any prosecution file historyassociated with same, any of same that is inconsistent with or inconflict with the present document, or any of same that may have alimiting affect as to the broadest scope of the claims now or laterassociated with the present document. By way of example, should there beany inconsistency or conflict between the description, definition,and/or the use of a term associated with any of the incorporatedmaterial and that associated with the present document, the description,definition, and/or the use of the term in the present document shallprevail.

In closing, it is to be understood that the embodiments of theapplication disclosed herein are illustrative of the principles of theembodiments of the application. Other modifications that may be employedmay be within the scope of the application. Thus, by way of example, butnot of limitation, alternative configurations of the embodiments of theapplication may be utilized in accordance with the teachings herein.Accordingly, embodiments of the present application are not limited tothat precisely as shown and described.

I claim:
 1. A system comprising: at least one non-transitorycomputer-readable storage medium including a set of instructions; atleast one processor in communication with the at least onenon-transitory computer-readable storage medium, wherein when executingthe instructions, the at least one processor is configured to cause thesystem to: determine an imaging gradient parameter according to ascanning protocol; determine a time origin for gradient momentcalculation and a target condition for a flow sensitive gradient blockassociated with the time origin; determine a parameter of a flowsensitive gradient block according to the target condition, the flowsensitive gradient block including at least one flow sensitive gradient,the parameter of the flow sensitive gradient block including at leastone duration and at least one amplitude value of the at least one flowsensitive gradient; modify the parameter of the flow sensitive gradientblock by adjusting a duration of the flow sensitive gradient blockiteratively, wherein the duration of the flow sensitive gradient blockis determined based on the at least one duration of the at least oneflow sensitive gradient; and adjusting the imaging gradient parameter byinserting the modified flow sensitive gradient block into the imaginggradient parameter.
 2. The system of claim 1, wherein the flow sensitivegradient block further includes a first flow sensitive gradient and asecond flow sensitive gradient.
 3. The system of claim 1, wherein thetarget condition further includes a target zeroth-order gradient momentand a target first-order gradient moment associated with the flowsensitive gradient block.
 4. The system of claim 2, wherein the at leastone processor is further configured to cause the system to: initialize aduration T and a time difference ΔT associated with the flow sensitivegradient block, the duration T being a time length of the flow sensitivegradient block, the time difference ΔT being a distance between the timeorigin and a time point of the flow sensitive gradient block.
 5. Thesystem of claim 4, wherein the at least one processor is furtherconfigured to cause the system to: determine a first amplitude value ofthe first flow sensitive gradient and a second amplitude value of thesecond flow sensitive gradient; determine the first amplitude value andthe second amplitude value are equal to or less than a threshold; and inresponse to the determination that the first amplitude value and thesecond amplitude value are equal to or less than the threshold,determine the current duration T as the duration of the flow sensitivegradient block.
 6. The system of claim 5, wherein the at least oneprocessor is further configured to cause the system to: determine thefirst amplitude value and the second amplitude value are larger than thethreshold; and in response to the determination that the first amplitudevalue and the second amplitude value are larger than the threshold,adjusting the current duration T of the flow sensitive gradient block,wherein the adjusted duration T is designated as the duration of theflow sensitive gradient block in a next iterative operation.
 7. Thesystem of claim 5, wherein: the parameter of the flow sensitive gradientblock further includes a component on a slice selecting axis, acomponent on a phase encoding axis, and a component on a readoutcoordinate axis, and the at least one processor is further configured tocause the system to: determine a final duration Ts′ associated with theslice selecting axis, a final duration Tp′ associated with the phaseencoding axis, and a final duration Tr′ associated with the readoutcoordinate axis, respectively; and determine a shared duration T′ forthe slice selecting axis, the phase encoding axis, and the readoutcoordinate axis based on the final durations, wherein the sharedduration T′ is designated as the duration of flow sensitive gradientblock.
 8. The system of claim 1, wherein the scanning protocol isassociated to a pulse sequence of one or more echoes.
 9. The system ofclaim 1, wherein the flow sensitive gradient block is further used toperform at least one function of flow encoding, flow compensation, orflow dephasing.
 10. The system of claim 7, wherein to determine a sharedduration T′ for the phase encoding axis slice selecting axis, the phaseencoding axis, and the readout coordinate axis based on the finaldurations, the at least one processor is further configured to cause thesystem to: determine a maximum value of the final durations, Tr′, Tp′and Ts′, as the shared duration T′.
 11. A method implemented on acomputing device having at least one processor, at least onecomputer-readable storage medium, and a communication port connected toan imaging device, the method comprising: determining an imaginggradient parameter for an echo in an imaging sequence; determining atime origin for gradient moment calculation based on the imaginggradient parameter; obtaining at least a target zeroth-order gradientmoment and a target first-order gradient moment corresponding to thetime origin; determining a parameter of a flow sensitive gradient blockwith respect to the target zeroth-order gradient moment and the targetfirst-order gradient moment, the flow sensitive gradient block includingat least one flow sensitive gradient, the parameter of the flowsensitive gradient block including at least one duration and at leastone amplitude value of the at least one flow sensitive gradient;modifying the parameter of the flow sensitive gradient block byadjusting a duration of the flow sensitive gradient block iteratively,wherein the duration of the flow sensitive gradient block is determinedbased on the at least one duration of the at least one flow sensitivegradient; and updating the imaging gradient parameter by inserting themodified flow sensitive gradient block into the imaging gradientparameter.
 12. The method of claim 11, wherein the imaging sequence is asingle-echo sequence, and the first flow sensitive gradient blockcomprising a single-pulse field gradient or a double-pulse fieldgradient.
 13. The method of claim 12, wherein the flow sensitivegradient block includes a first sensitive gradient and a secondsensitive gradient, further comprising: initializing a duration T and atime difference ΔT associated with the flow sensitive gradient block,the duration T being a time length of the flow sensitive gradient block,the time difference ΔT being a distance between the time origin and atime point of the flow sensitive gradient block.
 14. The method of claim13, further comprising: determining a first amplitude value of the firstflow sensitive gradient and a second amplitude value of the second flowsensitive gradient; determining the first amplitude value and the secondamplitude value equal to or less than a threshold; and in response tothe determination that the first amplitude value and the secondamplitude value are equal to or less than the threshold, determining thecurrent duration T as the duration of the flow sensitive gradient block.15. The method of claim 14, further comprising: determining the firstamplitude value and the second amplitude value are larger than thethreshold; and in response to the determination that the first amplitudevalue and the second amplitude value are larger than the threshold,adjusting the current duration T of the flow sensitive gradient block,wherein the adjusted duration T is designated as the duration of theflow sensitive gradient block in a next iterative operation.
 16. Themethod of claim 15, wherein the parameter of the flow sensitive gradientblock further includes a component on a slice selecting axis, acomponent on a phase encoding axis, and a component on a readoutcoordinate axis, further comprising: determining a final duration Ts′associated with the slice selecting axis, a final duration Tp′associated with the phase encoding axis, and a final duration Tr′associated with the readout coordinate axis, respectively; anddetermining a shared duration T′ for the slice selecting axis, the phaseencoding axis, and the readout coordinate axis based on the finaldurations.
 17. The method of claim 11, wherein the imaging sequencefurther comprises a second echo, and the method further comprising:determining an imaging gradient parameter for the second echo;determining a second time origin for gradient moment calculation basedon the imaging gradient parameter for the second echo; obtaining atleast a target zeroth-order gradient moment and a target first-ordergradient moment corresponding to the second time origin; determining asecond parameter of a second flow sensitive gradient block with respectto the target zeroth-order gradient moment and the target first-ordergradient moment, the second flow sensitive gradient block including atleast one flow sensitive gradient, the second parameter of the secondflow sensitive gradient block including at least one duration and atleast one amplitude value of the at least one flow sensitive gradient;modifying the second parameter of the second flow sensitive gradientblock by adjusting a duration of the second flow sensitive gradientblock iteratively, wherein the duration of the second flow sensitivegradient block is determined based on the at least one duration of theat least one flow sensitive gradient corresponding to the second flowsensitive gradient block; and updating the imaging gradient parameter byinserting the modified second flow sensitive gradient block into theimaging gradient parameter.
 18. The method of claim 17, wherein thetarget zeroth-order gradient moment and the target first-order gradientmoment corresponding to the time origin are independent of the targetzeroth-order gradient moment and the target first-order gradient momentcorresponding to the second time origin.
 19. The method of claim 11,further comprising: exciting nuclear spins in a volume of a subjectbased on the updated imaging gradient parameter, wherein the volumecomprises a flow; acquiring magnetic resonance signals for the volume;and generating a magnetic resonance image of the volume with the flowbased on the magnetic resonance signals.
 20. A non-transitory computerreadable medium embodying a computer program product, the computerprogram product comprising instructions configured to cause a computingdevice to: determine an imaging gradient parameter for one or moreechoes in an imaging sequence; determine one or more time origins forgradient moment calculation based on the gradient parameter; obtain oneor more target zeroth-order gradient moments and one or more targetfirst-order gradient moments corresponding to the one or more timeorigins, respectively; determine one or more parameters of one or moreflow sensitive gradient blocks with respect to the one or more targetzeroth-order gradient moments and the one or more target first-ordergradient moments, wherein each of the one or more flow sensitivegradient blocks includes at least one flow sensitive gradient, theparameter of each of the one or more flow sensitive gradient blocksincludes at least one duration and at least one amplitude value of theat least one flow sensitive gradient; modify each of the one or moreparameters of the one or more flow sensitive gradient blocks byadjusting a corresponding duration of the flow sensitive gradient blockiteratively, wherein the duration of the flow sensitive gradient blockis determined based on the at least one duration of the at least oneflow sensitive gradient corresponding to the flow sensitive gradientblock; and update the image gradient parameter according to the modifiedone or more parameters of the one or more flow sensitive gradientblocks.